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* feat: add a restricted and supervised Claude Code runner Preserve configured authentication and models while enforcing tool access, strict completion JSON, bounded output and process cleanup. Cover argv, failure handling, session metadata and Windows process containment. * feat: route outside reviews by harness and migrate wrapper installs Use Claude Code from Codex and Codex from other supported hosts, with shared invocation rendering, positive gate validation and per-phase provenance. Rename /claude to /claude-code, repair managed shared and copied installations safely, and generate native Kiro skills. Add installed-workflow, failure-injection and live cross-harness regression coverage. * test: recognize CEO mode labels without terminal spacing The paid workflow rendered SCOPEEXPANSION at option 4, but its driver required a literal space. Match the leading mode title without cursor-spacing artifacts and ignore adjacent preview text. Preserve missing-target failures and downstream posture assertions. * test: isolate plan-count fixtures before starting review workflows Seed the complete test plan in a private git repository before launching Claude, so a bare slash command cannot review the live workspace while a delayed fixture message remains queued. Preserve count thresholds, parsers and budgets. Add initial-context and installed-discovery tests, and retain startup/terminal diagnostics on failed evaluations. * test: stabilize review fixtures and Claude eval startup Preserve source boundaries in workflow judge inputs, isolate CEO mode plans, and wait for interactive trust input readiness. Keep startup failure evidence and retain existing models, budgets, and assertions. Co-Authored-By: OpenAI Codex <noreply@openai.com> * test: classify collapsed review modes and isolate seeded findings Keep review questions out of the setup count when terminal cursor positioning removes spaces. State existing webhook safeguards so the five-finding control measures its seeded defects without accidental extra security and concurrency gaps. Preserve question bands and the paired control. Co-Authored-By: OpenAI Codex <noreply@openai.com> * test: isolate browser daemon state across free shards Co-Authored-By: OpenAI Codex <noreply@openai.com> * test: stabilize native review counting and interactive navigation Co-Authored-By: OpenAI Codex <noreply@openai.com> * chore: prepare v1.82.0.0 release Co-Authored-By: OpenAI Codex <noreply@openai.com> * fix: eliminate browser and process-cleanup test flakes Pin every CI surface to Bun 1.4.0 to avoid extra-stdio finalizers closing reused live sockets. Add an isolated GC/listener regression that fails on Bun 1.3.13, and prevent coordinated rollback to an affected CI runtime. Check renderer cleanup against the render's own staging directory so concurrent renders cannot invalidate the assertion. Make the no-pgrep process-tree walk tolerate disappearing /proc entries, and synchronize its test fixture through child readiness and pipe EOF instead of sleeps. Validation: 9,157 passed, 31 skipped, zero failures across 556 files with retries disabled. Build, all-host generation freshness, and skill checks passed. All three races have failing-before/passing-after regressions. * fix: count completed native review questions in evals * fix: drive review navigation from confirmed native choices * fix: require complete section-loading eval reports * test: isolate telemetry HTTP transport from local assertions * fix: keep review input on the active native question * test: let tunnel revocation daemon choose an available port * test: allocate available ports for pairing and watchdog fixtures * fix: stabilize planning eval navigation and phase reporting * test: isolate installed runtime paths in planning evals * test: stabilize review evidence and concurrent refresh fixtures * fix: resolve design findings before editing the plan * fix: honor and persist disabled outside plan reviews * fix: preserve planning decisions and terminal evidence Load installed host reviews at autoplan phase entry and wait for completed reviewers and saved artifacts. Reuse approved remedies while preserving individual finding decisions. Drive interactive evals from the current terminal viewport, bind native questions across scrolling, and require complete native report evidence. Cover captured stale menus, permission lifecycles, setup classification, and disabled-review tool availability with deterministic regressions. Advance release metadata and the upgrade migration to the unclaimed 1.83.0.0 slot. * fix: drive native review questions and preserve current plans Use the native single-choice keyboard protocol and current terminal viewport, with per-question navigation inside packets and completed-call coverage. Keep permissions, multi-select menus, and Submit controls distinct. Send Autoplan reviewers the amended implementation plan, keep its review record separate, and supply retained application contracts in the chain fixture. Clarify individual DevEx decisions and complete CEO fix options; use one active plan destination for the section-loading report. * fix: preserve complete plan-review decisions * fix: recognize native plan dialogs and reviewer controls * fix: preserve review decisions and phase completion * fix: recognize completed reviews without losing findings * fix: preserve review continuity and native eval completion * test: fix native review completion and eval retry isolation * test: handle native review menus and complete eval fixtures * test: fix native review setup, completion, and isolation failures * test: limit native skill discovery to runtime assets * fix: bind Autoplan reviews to full ordered phase inputs * test: fix planning eval routing, counting, and timeout handling * chore: advance queued release to v1.84.0.0 * fix: preserve complete review inputs and planning decisions * fix: reconcile review approvals and preserve phase obligations * fix: preserve review obligations and unblock eval permissions Carry recorded Autoplan requirements into blind phase inputs, require Eng review approvals before exit, and exercise combined asynchronous flows in CEO reviews. Correct native finding and handoff classification and unblock repeated report edits using scoped request identities. * fix: retain plan requirements and complete native review dialogs * fix: complete native review prompts and retain plan references * fix: preserve review inputs and classify native eval evidence * fix: check competing completion orders in CEO reviews * fix: recognize review decisions and require phase methodology Require the current phase methodology before Autoplan snapshots. Correct substantive decision, closed handoff, and cache-finding classification, and honor the recommended implementation approach in native review dialogs. Add captured-transcript regressions without changing review thresholds, provider models, retries, or deadlines. * test: bind native review decisions and close completed handoffs * fix: complete review dialogs and verify methodology delivery * fix: preserve review evidence and unblock native eval prompts * fix: handle native review question completions * fix: recognize native review narration and controls * fix: count native review decisions and isolate eval fixtures * test: verify seeded review coverage and current artifact permissions * test: isolate model and brain-aware skill renders * fix: repair native workflow evaluation and clarify review steps * fix: stabilize workflow eval evidence and review guidance * test: repair native workflow observation and fixture isolation * fix: recognize completed workflow evidence and owned skill reads * test: repair seeded workflow delivery and completion evidence * test: recognize current review evidence across native forms * test: handle native review variants and permission redraws * fix: honor review preferences and recognize native eval evidence * test: recognize completed review decisions and queued permissions * test: match current review contracts and partial-line edits * test: recognize completed workflow evidence and bounded human waits * fix: preserve review entry gates and native eval interactions * fix: recognize native workflow evidence and preserve review gates * test: recognize current review evidence and preconfigure workflow fixtures * test: recognize completed review findings and scoped artifact permissions * fix: stabilize native workflow review and permission evidence * fix: recognize current review evidence and scoped edit confirmations Clarify Design and engineering review entry instructions and Design scoring. Recognize required legacy coverage and public Autoplan completion recaps. Bind the pending Edit confirmation to its exact file, ordered digest, and one-request approval when a preceding command display remains visible. Keep reviews within their existing size limits and preserve scope gates when extracting workflow fixtures from either supported preamble header. Keep failure outcomes, review thresholds, provider choices, and eval budgets. * fix: recover review workflow progress and eval evidence * fix: recognize valid review evidence and scope selection * test: fix review evidence parsing and repeated artifact prompts * test: recognize valid review decisions and pending native cards * fix(plan-eng-review): keep final navigation consistent with approved tasks * test: recognize valid review evidence and bind legacy diff requests * fix: stabilize review eval evidence and harness repair guidance * docs: update project documentation for v1.85.0.0 Co-Authored-By: OpenAI Codex <noreply@openai.com> * test: fix Windows CI fixtures and credential scan Rebase captured JSON values and filesystem evidence using the appropriate path convention. Compile native fake CLIs on Windows and synchronize pipe holder readiness, with cleanup retained when assertions fail. Assemble synthetic credential fixtures at runtime so the added-line scan keeps enforcing the same gate without flagging its own rejection controls. Discover generated skills directly for the empty-find regression check, avoiding a recursive scan through saved evaluation artifacts and dependencies. * fix: preserve source renders on Windows Compare canonical generator paths using native separators so an output sidecar pointing at the source cannot overwrite its skill or metadata. Keep the regression fixture isolated from the real checkout and expose freshness diagnostics before asserting subprocess status. Detach Windows drain-test pipe holders from the fake provider's automatic child cleanup while preserving the enclosing runner job and its assertions. * fix: clarify outside review fallback and CEO decisions Render one applicable own-harness fallback path and retain native review, disabled policy, and missing-coverage semantics. Align report field names and mode labels, and make the existing per-cut scope approval explicit. Regenerate skill outputs and keep the workflow judge's model, thresholds, and retry policy unchanged. * chore: move release to free version slot (v1.86.0.0) PR #2852 now claims v1.85.0.0. Align the release metadata and rename migration so upgrades from that version still receive it. Co-Authored-By: OpenAI Codex <noreply@openai.com> * fix: include engineering review prerequisites and restore branch context * fix: recognize coverage diagrams and clarify design review instructions * fix: preserve file identities and join Windows test processes --------- Co-authored-by: OpenAI Codex <noreply@openai.com>
413 lines
35 KiB
JSON
413 lines
35 KiB
JSON
{
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"devex": {
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"sessionId": "306e0de6-6557-43cf-8502-f320c689b3ad",
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"calls": [
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{
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"sessionId": "306e0de6-6557-43cf-8502-f320c689b3ad",
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"toolUseId": "toolu_01PF1kGiAidK2jLcnwa63hkH",
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"questions": [
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{
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"question": "D1 — Does this empathy narrative match the real EvalKit onboarding experience? <gstack-qid:plan-devex-review-empathy-narrative>\n\nI traced the actual path from README and docs. Your ML engineer persona today:\n\nT+0:00 — Runs `python -m pip install evalkit==2.0.0b1`. Installs fine.\nT+1:00 — Sets EVALKIT_API_KEY.\nT+1:30 — README says: \"follow the quickstart's command: python examples/first_eval.py\". Runs it.\nT+1:35 — Error: \"can't open file 'examples/first_eval.py': No such file or directory\"\nT+1:40 — Scrolls README, no explanation. Spots python -m evalkit.demo and tries it.\nT+1:45 — stderr: \"Waiting for CI check: 0s elapsed of 300s\"\nT+6:45 — \"CI check completed.\"\nT+6:50 — Finally: example 1: score=0.80 / example 2: score=1.00 / overall: score=0.90\n\nResult: ~7 minutes. The quickstart pointed at a file absent from the package. The demo blocked 5 minutes on an unexplained network hold. Target is under 2 minutes. Does this match reality?",
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"header": "Empathy check",
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"multiSelect": false,
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"options": [
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{
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"label": "Accurate — proceed (Recommended)",
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"description": "This is correct. Use this as the empathy baseline for all 8 review passes."
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},
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{
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"label": "Partly wrong — correct it",
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"description": "Some details are off. You'll clarify and I'll update before proceeding."
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},
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{
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"label": "Wrong — actual experience differs",
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"description": "The real onboarding path is substantially different. Describe the actual flow."
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}
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]
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}
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],
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"answered": true,
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"failed": false,
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"answers": {
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"D1 — Does this empathy narrative match the real EvalKit onboarding experience? <gstack-qid:plan-devex-review-empathy-narrative>\n\nI traced the actual path from README and docs. Your ML engineer persona today:\n\nT+0:00 — Runs `python -m pip install evalkit==2.0.0b1`. Installs fine.\nT+1:00 — Sets EVALKIT_API_KEY.\nT+1:30 — README says: \"follow the quickstart's command: python examples/first_eval.py\". Runs it.\nT+1:35 — Error: \"can't open file 'examples/first_eval.py': No such file or directory\"\nT+1:40 — Scrolls README, no explanation. Spots python -m evalkit.demo and tries it.\nT+1:45 — stderr: \"Waiting for CI check: 0s elapsed of 300s\"\nT+6:45 — \"CI check completed.\"\nT+6:50 — Finally: example 1: score=0.80 / example 2: score=1.00 / overall: score=0.90\n\nResult: ~7 minutes. The quickstart pointed at a file absent from the package. The demo blocked 5 minutes on an unexplained network hold. Target is under 2 minutes. Does this match reality?": "Accurate — proceed (Recommended)"
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},
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"unansweredQuestionIndices": [],
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"answeredAt": "2026-09-09T05:56:14.770Z"
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},
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{
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"sessionId": "306e0de6-6557-43cf-8502-f320c689b3ad",
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"toolUseId": "toolu_01BcgUMDvFU4UsB9GrrdsVmY",
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"questions": [
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{
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"question": "D2 — Journey Stage HELLO WORLD: The quickstart file is absent from the published package. <gstack-qid:plan-devex-review-missing-quickstart>\n\nThe README says the first command after install is `python examples/first_eval.py`. But docs/package-contents.txt confirms: \"The quickstart references examples/first_eval.py, but that file is absent from both the published package and the release examples archive.\"\n\nEvery developer who follows the README gets a file-not-found error as their first interaction with EvalKit. This is a P0 blocker — the primary onboarding path is broken before any evaluation runs. The demo module (python -m evalkit.demo) works, but the README leads here first.\n\nStakes if we don't fix: First impression is a crash. The developer doesn't know if it's their fault or the SDK's.\n\nRecommendation: A — replace the quickstart reference in README with the working demo command, because the demo is already packaged and produces the right output.\n\nCompleteness: A=9/10, B=7/10, C=4/10",
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"header": "Missing file",
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"multiSelect": false,
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"options": [
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{
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"label": "Fix README to point to demo (Recommended)",
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"description": "Replace `python examples/first_eval.py` with `python -m evalkit.demo` as the primary quickstart command. One-line README edit. Completeness: 9/10"
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},
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{
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"label": "Add first_eval.py to package",
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"description": "Write and include examples/first_eval.py in the published package so the README stays correct. Requires authoring the file and updating the package manifest. Completeness: 7/10"
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},
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{
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"label": "Leave both, add a note",
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"description": "Keep the README reference but add a note that the file is not included and point to the demo as an alternative. Lowest effort but perpetuates the confusion. Completeness: 4/10"
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}
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]
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}
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],
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"answered": true,
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"failed": false,
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"answers": {
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"D2 — Journey Stage HELLO WORLD: The quickstart file is absent from the published package. <gstack-qid:plan-devex-review-missing-quickstart>\n\nThe README says the first command after install is `python examples/first_eval.py`. But docs/package-contents.txt confirms: \"The quickstart references examples/first_eval.py, but that file is absent from both the published package and the release examples archive.\"\n\nEvery developer who follows the README gets a file-not-found error as their first interaction with EvalKit. This is a P0 blocker — the primary onboarding path is broken before any evaluation runs. The demo module (python -m evalkit.demo) works, but the README leads here first.\n\nStakes if we don't fix: First impression is a crash. The developer doesn't know if it's their fault or the SDK's.\n\nRecommendation: A — replace the quickstart reference in README with the working demo command, because the demo is already packaged and produces the right output.\n\nCompleteness: A=9/10, B=7/10, C=4/10": "Fix README to point to demo (Recommended)"
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},
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"unansweredQuestionIndices": [],
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"answeredAt": "2026-09-09T05:56:28.814Z"
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},
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{
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"sessionId": "306e0de6-6557-43cf-8502-f320c689b3ad",
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"toolUseId": "toolu_018Xrf5Na2k8ebPUaMS6Hj3G",
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"questions": [
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{
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"question": "D3 — Journey Stage HELLO WORLD: The 5-minute mandatory CI block makes the under-2-minute TTHW target unreachable. <gstack-qid:plan-devex-review-tthw-ci-block>\n\nThe plan retains the first-run CI gate (docs/current-contracts.md): \"blocks for five minutes before returning an evaluation result. There is no skip flag or offline first-run path.\" The README confirms: \"Like every first evaluation, it currently waits for the mandatory CI check.\"\n\ndocs/benchmarks.md shows the agreed target is under 2 minutes. Competitor A already hits 2 minutes. The 5-minute block applies to EVERY first-time developer, including the demo (`python -m evalkit.demo`). No matter how fast install + auth runs, the gate adds 5 minutes.\n\nThe plan retains this gate. That makes the under-2-minute target a documented goal the plan cannot achieve as written.\n\nStakes if we don't fix: The benchmarks.md target is false. Developers wait 5x longer than the stated goal. The plan ships with a known broken promise.\n\nRecommendation: A — add a demo-mode skip flag that bypasses the CI check for bundled sample data, so `python -m evalkit.demo` is fast while real evaluations keep the gate. The magical moment should not cost 5 minutes.\n\nCompleteness: A=9/10, B=6/10, C=3/10",
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"header": "TTHW target",
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"multiSelect": false,
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"options": [
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{
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"label": "Add demo-mode CI skip flag (Recommended)",
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"description": "Exempt `python -m evalkit.demo` (bundled sample data only) from the mandatory CI check. Real evaluations keep the gate. TTHW for onboarding becomes ~1 minute. Completeness: 9/10"
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},
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{
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"label": "Revise target in benchmarks.md",
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"description": "Update the documented target to reflect reality: 6-7 minutes. Honest, but accepts losing to all three peer SDKs and abandons the competitive goal. Completeness: 6/10"
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},
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{
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"label": "Leave as-is, document the wait",
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"description": "Keep the gate, keep the target, and add a note in README that first-run takes 5 minutes. Developers are warned but still wait. Target remains broken. Completeness: 3/10"
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}
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]
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}
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],
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"answered": true,
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"failed": false,
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"answers": {
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"D3 — Journey Stage HELLO WORLD: The 5-minute mandatory CI block makes the under-2-minute TTHW target unreachable. <gstack-qid:plan-devex-review-tthw-ci-block>\n\nThe plan retains the first-run CI gate (docs/current-contracts.md): \"blocks for five minutes before returning an evaluation result. There is no skip flag or offline first-run path.\" The README confirms: \"Like every first evaluation, it currently waits for the mandatory CI check.\"\n\ndocs/benchmarks.md shows the agreed target is under 2 minutes. Competitor A already hits 2 minutes. The 5-minute block applies to EVERY first-time developer, including the demo (`python -m evalkit.demo`). No matter how fast install + auth runs, the gate adds 5 minutes.\n\nThe plan retains this gate. That makes the under-2-minute target a documented goal the plan cannot achieve as written.\n\nStakes if we don't fix: The benchmarks.md target is false. Developers wait 5x longer than the stated goal. The plan ships with a known broken promise.\n\nRecommendation: A — add a demo-mode skip flag that bypasses the CI check for bundled sample data, so `python -m evalkit.demo` is fast while real evaluations keep the gate. The magical moment should not cost 5 minutes.\n\nCompleteness: A=9/10, B=6/10, C=3/10": "Add demo-mode CI skip flag (Recommended)"
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},
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"unansweredQuestionIndices": [],
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"answeredAt": "2026-09-09T05:56:54.414Z"
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},
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{
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"sessionId": "306e0de6-6557-43cf-8502-f320c689b3ad",
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"toolUseId": "toolu_01XoZ2ZdG3rGW5Ssh8ZttgU3",
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"questions": [
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{
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"question": "D4 — Pass 2 API Design: `run_eval` and `run_batch` take the same two arguments in opposite order. <gstack-qid:plan-devex-review-arg-order>\n\ndocs/api.md shows:\n- `run_eval(dataset, evaluator)` — dataset first\n- `run_batch(evaluator, dataset)` — evaluator first\n\nBoth describe the same concepts. The plan notes \"The reversed positional order is intentional in the current draft; neither function requires keyword arguments.\"\n\nFor an ML engineer using both functions in the same codebase, this is a muscle memory trap. A dev who writes `run_eval(my_dataset, my_eval)` will write `run_batch(my_dataset, my_eval)` by reflex — silently passing the wrong values in the wrong order, with no type error because both arguments are the same type.\n\nThe Pit of Success test: make the right thing easy, the wrong thing hard. This API makes a silent wrong call easy.\n\nStakes: Logic bugs that don't surface at runtime, only in evaluation results. \"Why are my batch scores wrong?\" is a hard debug.\n\nRecommendation: A — standardize on `(dataset, evaluator)` order in both functions, because dataset is the primary noun (what you're evaluating), evaluator is the tool. Both should require keyword arguments or be consistently ordered.\n\nCompleteness: A=10/10, B=7/10, C=4/10",
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"header": "Arg order",
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"multiSelect": false,
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"options": [
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{
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"label": "Standardize order to (dataset, evaluator) (Recommended)",
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"description": "Fix run_batch to match run_eval's order. Breaking change for v2, so ideal to ship before beta release. Add keyword-argument requirement or deprecation shim for the old order. Completeness: 10/10"
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},
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{
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"label": "Require keyword arguments in both",
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"description": "Leave the positional order inconsistency but require callers to use keyword arguments (`run_batch(evaluator=e, dataset=d)`). Eliminates silent wrong-order calls without changing argument order. Completeness: 7/10"
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},
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{
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"label": "Leave intentional, add docs warning",
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"description": "Keep the reversed order as-is but add a prominent note in the API reference. Preserves current behavior, relies on developers reading docs carefully. Completeness: 4/10"
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}
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]
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}
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],
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"answered": true,
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"failed": false,
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"answers": {
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"D4 — Pass 2 API Design: `run_eval` and `run_batch` take the same two arguments in opposite order. <gstack-qid:plan-devex-review-arg-order>\n\ndocs/api.md shows:\n- `run_eval(dataset, evaluator)` — dataset first\n- `run_batch(evaluator, dataset)` — evaluator first\n\nBoth describe the same concepts. The plan notes \"The reversed positional order is intentional in the current draft; neither function requires keyword arguments.\"\n\nFor an ML engineer using both functions in the same codebase, this is a muscle memory trap. A dev who writes `run_eval(my_dataset, my_eval)` will write `run_batch(my_dataset, my_eval)` by reflex — silently passing the wrong values in the wrong order, with no type error because both arguments are the same type.\n\nThe Pit of Success test: make the right thing easy, the wrong thing hard. This API makes a silent wrong call easy.\n\nStakes: Logic bugs that don't surface at runtime, only in evaluation results. \"Why are my batch scores wrong?\" is a hard debug.\n\nRecommendation: A — standardize on `(dataset, evaluator)` order in both functions, because dataset is the primary noun (what you're evaluating), evaluator is the tool. Both should require keyword arguments or be consistently ordered.\n\nCompleteness: A=10/10, B=7/10, C=4/10": "Standardize order to (dataset, evaluator) (Recommended)"
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},
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"unansweredQuestionIndices": [],
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"answeredAt": "2026-09-09T05:57:22.039Z"
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},
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{
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"sessionId": "306e0de6-6557-43cf-8502-f320c689b3ad",
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"toolUseId": "toolu_01Y1XAbDXc99z6tzdt5eXBXG",
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"questions": [
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{
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"question": "D5 — Pass 3 Error Messages: The auth error gives developers nothing to act on. <gstack-qid:plan-devex-review-auth-error>\n\ndocs/api.md states: \"For an invalid API key, the SDK raises `AuthError('request failed')`.\nThere is no authentication error code, explanation of the cause, or instruction for replacing the key. The plan retains this message.\"\n\nAuth errors are the single most common first-run failure mode for SDK developers. \"request failed\" tells the developer nothing: not what request, not why it failed, not what to check. They'll grep their code looking for what they broke.\n\nThe DX First Principle: every error = problem + cause + fix. Current message delivers zero of three.\n\nComparison: A Stripe auth failure returns `{\"error\": {\"code\": \"api_key_invalid\", \"message\": \"No API key provided.\", \"type\": \"invalid_request_error\"}}`.\n\nStakes: Developers with a wrong or missing key get a useless message. They try again, check env vars three times, maybe open a support ticket. The fix is one line.\n\nRecommendation: A — change the error message to include cause and fix, because DX POLISH means bulletproofing every touchpoint and this is the highest-traffic error path.\n\nCompleteness: A=10/10, B=6/10",
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"header": "Auth error",
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"multiSelect": false,
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"options": [
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{
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"label": "Fix error message to include cause + fix (Recommended)",
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"description": "Change AuthError message to something like: \"Authentication failed: API key invalid or missing. Check that EVALKIT_API_KEY is set and valid. See docs/api.md for key setup.\" Completeness: 10/10"
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},
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{
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"label": "Add error code only, keep existing message",
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"description": "Add a machine-readable error code (e.g. AuthError code='auth_key_invalid') without rewriting the human message. Useful for programmatic handling but still unhelpful for the developer reading it. Completeness: 6/10"
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},
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{
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"label": "Leave as-is (plan's current position)",
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"description": "Keep AuthError('request failed'). The plan explicitly retains this. Requires accepting that auth failures are invisible to developers. Completeness: 3/10"
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}
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]
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}
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],
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"answered": true,
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"failed": false,
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"answers": {
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"D5 — Pass 3 Error Messages: The auth error gives developers nothing to act on. <gstack-qid:plan-devex-review-auth-error>\n\ndocs/api.md states: \"For an invalid API key, the SDK raises `AuthError('request failed')`.\nThere is no authentication error code, explanation of the cause, or instruction for replacing the key. The plan retains this message.\"\n\nAuth errors are the single most common first-run failure mode for SDK developers. \"request failed\" tells the developer nothing: not what request, not why it failed, not what to check. They'll grep their code looking for what they broke.\n\nThe DX First Principle: every error = problem + cause + fix. Current message delivers zero of three.\n\nComparison: A Stripe auth failure returns `{\"error\": {\"code\": \"api_key_invalid\", \"message\": \"No API key provided.\", \"type\": \"invalid_request_error\"}}`.\n\nStakes: Developers with a wrong or missing key get a useless message. They try again, check env vars three times, maybe open a support ticket. The fix is one line.\n\nRecommendation: A — change the error message to include cause and fix, because DX POLISH means bulletproofing every touchpoint and this is the highest-traffic error path.\n\nCompleteness: A=10/10, B=6/10": "Fix error message to include cause + fix (Recommended)"
|
|
},
|
|
"unansweredQuestionIndices": [],
|
|
"answeredAt": "2026-09-09T05:57:45.639Z"
|
|
},
|
|
{
|
|
"sessionId": "306e0de6-6557-43cf-8502-f320c689b3ad",
|
|
"toolUseId": "toolu_016eEvDGhGseLrg8LRLyAnDN",
|
|
"questions": [
|
|
{
|
|
"question": "D6 — Pass 5 Upgrade Path: `Client.evaluate()` is removed in v2 with no migration path. <gstack-qid:plan-devex-review-v1-migration>\n\ndocs/api.md: \"Version 1 exposes `Client.evaluate()`. Version 2 replaces it with `Client.run()` and removes the old name immediately. No compatibility alias, deprecation warning, migration guide, or codemod is provided.\"\n\nAny v1 user who upgrades gets `AttributeError: 'Client' object has no attribute 'evaluate'` with no context — the error tells them nothing about `Client.run()` or why the method disappeared.\n\nThis contradicts the SDK's own stated values: docs/current-contracts.md says \"All other errors already identify the cause, relevant argument or file, and an actionable fix.\" The upgrade path is the one place where this standard is violated.\n\nFor a beta SDK, a breaking rename without a shim is acceptable — but a helpful error message at the call site is not optional. Upgrade fear is a leading cause of SDK abandonment.\n\nStakes: v1 users hit an opaque error. They file issues instead of upgrading. Migration time grows from \"5 minutes\" to \"I need to figure out what changed.\"\n\nRecommendation: A — add a deprecated-method shim that raises a helpful AttributeError, because it's one function and it makes the upgrade self-documenting.\n\nCompleteness: A=9/10, B=7/10, C=4/10",
|
|
"header": "v1→v2 upgrade",
|
|
"multiSelect": false,
|
|
"options": [
|
|
{
|
|
"label": "Add deprecated shim with helpful error (Recommended)",
|
|
"description": "Keep `Client.evaluate()` but have it raise AttributeError: \"evaluate() was renamed to run() in v2. Replace: client.evaluate(data) -> client.run(data). See changelog for details.\" No behavior, just a self-documenting error. Completeness: 9/10"
|
|
},
|
|
{
|
|
"label": "Add migration guide only",
|
|
"description": "Write a v1-to-v2 migration guide in docs/ that lists the rename. Developers who read changelogs find it. Developers who don't still hit the opaque AttributeError. Completeness: 7/10"
|
|
},
|
|
{
|
|
"label": "Leave as-is (plan's current position)",
|
|
"description": "Keep the silent removal. Beta SDK, breaking changes expected. Developers can read the changelog. Completeness: 4/10"
|
|
}
|
|
]
|
|
}
|
|
],
|
|
"answered": true,
|
|
"failed": false,
|
|
"answers": {
|
|
"D6 — Pass 5 Upgrade Path: `Client.evaluate()` is removed in v2 with no migration path. <gstack-qid:plan-devex-review-v1-migration>\n\ndocs/api.md: \"Version 1 exposes `Client.evaluate()`. Version 2 replaces it with `Client.run()` and removes the old name immediately. No compatibility alias, deprecation warning, migration guide, or codemod is provided.\"\n\nAny v1 user who upgrades gets `AttributeError: 'Client' object has no attribute 'evaluate'` with no context — the error tells them nothing about `Client.run()` or why the method disappeared.\n\nThis contradicts the SDK's own stated values: docs/current-contracts.md says \"All other errors already identify the cause, relevant argument or file, and an actionable fix.\" The upgrade path is the one place where this standard is violated.\n\nFor a beta SDK, a breaking rename without a shim is acceptable — but a helpful error message at the call site is not optional. Upgrade fear is a leading cause of SDK abandonment.\n\nStakes: v1 users hit an opaque error. They file issues instead of upgrading. Migration time grows from \"5 minutes\" to \"I need to figure out what changed.\"\n\nRecommendation: A — add a deprecated-method shim that raises a helpful AttributeError, because it's one function and it makes the upgrade self-documenting.\n\nCompleteness: A=9/10, B=7/10, C=4/10": "Add deprecated shim with helpful error (Recommended)"
|
|
},
|
|
"unansweredQuestionIndices": [],
|
|
"answeredAt": "2026-09-09T05:58:11.250Z"
|
|
}
|
|
]
|
|
},
|
|
"eng": {
|
|
"sessionId": "4fc2a716-4122-4cd3-bc0e-1128cd9b9819",
|
|
"calls": [
|
|
{
|
|
"sessionId": "4fc2a716-4122-4cd3-bc0e-1128cd9b9819",
|
|
"toolUseId": "toolu_01YJ9RYv2tb9dKBYui3SMbnN",
|
|
"questions": [
|
|
{
|
|
"question": "D1 — Complexity check triggered: 12 files, 4 new classes. Reduce scope or proceed as-is? <gstack-qid:plan-eng-scope-complexity>",
|
|
"header": "Scope check",
|
|
"multiSelect": false,
|
|
"options": [
|
|
{
|
|
"label": "Proceed as-is (Recommended)",
|
|
"description": "Accept the full scope: AuthBroker, SessionMint, AuthCache facade, TokenStore, RequestPolicy across 12 files. Review all four classes for correctness and coupling, then implement the complete refactor."
|
|
},
|
|
{
|
|
"label": "Reduce scope first",
|
|
"description": "Propose a leaner version: keep AuthBroker + SessionMint as the core services, collapse AuthCache into direct adapter usage (the adapter already exists with all eviction/invalidation logic), and inline RequestPolicy and TokenStore logic rather than introducing standalone classes. Target: 7-8 files, 2 classes."
|
|
}
|
|
]
|
|
}
|
|
],
|
|
"answered": true,
|
|
"failed": false,
|
|
"answers": {
|
|
"D1 — Complexity check triggered: 12 files, 4 new classes. Reduce scope or proceed as-is? <gstack-qid:plan-eng-scope-complexity>": "Proceed as-is (Recommended)"
|
|
},
|
|
"unansweredQuestionIndices": [],
|
|
"answeredAt": "2026-09-09T05:56:31.324Z"
|
|
},
|
|
{
|
|
"sessionId": "4fc2a716-4122-4cd3-bc0e-1128cd9b9819",
|
|
"toolUseId": "toolu_018Pp3EC7wSd6EHLjWc58EDu",
|
|
"questions": [
|
|
{
|
|
"question": "D2 — Architecture Issue 1: Global mutable AuthCache shared between two services with no mutation serialization. How should we fix this? <gstack-qid:plan-eng-arch-shared-cache>",
|
|
"header": "Shared cache",
|
|
"multiSelect": false,
|
|
"options": [
|
|
{
|
|
"label": "Inject AuthCache via constructor (Recommended)",
|
|
"description": "Pass the AuthCache instance as a constructor argument to AuthBroker and SessionMint. No module-level singleton. Add a mutex or async queue (e.g. a simple promise-chain lock) to serialize writes. This makes the coupling explicit, testable, and prevents interleaved mutations from concurrent async flows."
|
|
},
|
|
{
|
|
"label": "Keep global export, add write serialization",
|
|
"description": "Retain the module-level singleton but wrap all mutating methods in an async mutex (e.g. using the 'async-mutex' package or a hand-rolled promise queue). Lower refactor surface, but the hidden global dependency remains, making unit testing harder and creating a subtle import-order hazard."
|
|
},
|
|
{
|
|
"label": "Keep as-is, document the risk",
|
|
"description": "Accept the race condition as acceptable for the current scale and add a code comment flagging it. Not recommended: the plan explicitly notes mutations are not serialized, and a cache holding auth tokens corrupted at write time is a security surface, not just a correctness issue."
|
|
}
|
|
]
|
|
}
|
|
],
|
|
"answered": true,
|
|
"failed": false,
|
|
"answers": {
|
|
"D2 — Architecture Issue 1: Global mutable AuthCache shared between two services with no mutation serialization. How should we fix this? <gstack-qid:plan-eng-arch-shared-cache>": "Inject AuthCache via constructor (Recommended)"
|
|
},
|
|
"unansweredQuestionIndices": [],
|
|
"answeredAt": "2026-09-09T05:56:53.399Z"
|
|
},
|
|
{
|
|
"sessionId": "4fc2a716-4122-4cd3-bc0e-1128cd9b9819",
|
|
"toolUseId": "toolu_01VwxtKsLQumQ7Ag869jNbBk",
|
|
"questions": [
|
|
{
|
|
"question": "D3 — Code Quality Issue 1: validateAndDispatch() swallows three distinct error classes across nested try/catch blocks. How should we address this? <gstack-qid:plan-eng-cq-error-swallow>",
|
|
"header": "Error handling",
|
|
"multiSelect": false,
|
|
"options": [
|
|
{
|
|
"label": "Refactor into typed error propagation (Recommended)",
|
|
"description": "Break validateAndDispatch() into 3-4 focused sub-functions (validateToken, dispatchPolicy, recordAudit etc.), each throwing or returning a typed Result<T, AuthError>. Replace catch-and-swallow with catch-log-rethrow at the entry point boundary only. This aligns with 'explicit over clever' and gives callers actionable error types. (human: ~3h / CC: ~20min)"
|
|
},
|
|
{
|
|
"label": "Log and rethrow in each catch, keep structure",
|
|
"description": "Minimal change: add logger.error() in each catch, then rethrow (or return a discriminated error enum). Keeps the 60-line function intact but stops silently swallowing failures. Faster, but doesn't fix the structural debt. (human: ~30min / CC: ~5min)"
|
|
}
|
|
]
|
|
}
|
|
],
|
|
"answered": true,
|
|
"failed": false,
|
|
"answers": {
|
|
"D3 — Code Quality Issue 1: validateAndDispatch() swallows three distinct error classes across nested try/catch blocks. How should we address this? <gstack-qid:plan-eng-cq-error-swallow>": "Refactor into typed error propagation (Recommended)"
|
|
},
|
|
"unansweredQuestionIndices": [],
|
|
"answeredAt": "2026-09-09T05:57:51.609Z"
|
|
},
|
|
{
|
|
"sessionId": "4fc2a716-4122-4cd3-bc0e-1128cd9b9819",
|
|
"toolUseId": "toolu_011quLsKZRH26s88RTtqZNgp",
|
|
"questions": [
|
|
{
|
|
"question": "D4 — Test Issue 1: No E2E or integration test planned for the cross-service auth flow (AuthBroker → IDP → AuthCache → SessionMint). Add one? <gstack-qid:plan-eng-test-e2e-auth>",
|
|
"header": "E2E coverage",
|
|
"multiSelect": false,
|
|
"options": [
|
|
{
|
|
"label": "Add E2E integration test for full auth flow (Recommended)",
|
|
"description": "Add one E2E test file (auth-flow.e2e.ts or similar) covering: (1) full token validation round-trip against a stubbed IDP, (2) concurrent requests from two tenants (validates mutex correctness), (3) logout triggers cache invalidation. This is the flow the plan's unit tests cannot adequately mock. (human: ~4h / CC: ~25min)"
|
|
},
|
|
{
|
|
"label": "Unit tests only, skip E2E",
|
|
"description": "Accept that unit tests with mocked IDP and mocked cache cover the plan's scope. The integration surface is small enough to trust. Risk: mutex correctness and IDP retry behavior are not verified until production. (human: 0 / CC: 0)"
|
|
}
|
|
]
|
|
}
|
|
],
|
|
"answered": true,
|
|
"failed": false,
|
|
"answers": {
|
|
"D4 — Test Issue 1: No E2E or integration test planned for the cross-service auth flow (AuthBroker → IDP → AuthCache → SessionMint). Add one? <gstack-qid:plan-eng-test-e2e-auth>": "Add E2E integration test for full auth flow (Recommended)"
|
|
},
|
|
"unansweredQuestionIndices": [],
|
|
"answeredAt": "2026-09-09T05:58:43.808Z"
|
|
},
|
|
{
|
|
"sessionId": "4fc2a716-4122-4cd3-bc0e-1128cd9b9819",
|
|
"toolUseId": "toolu_01ETKhG4zvAW4PURcXzHVMwh",
|
|
"questions": [
|
|
{
|
|
"question": "D5 — Performance Issue 1: 5 sequential IDP calls per token validation. Fix with Promise.all in this PR or defer? <gstack-qid:plan-eng-perf-idp-parallel>",
|
|
"header": "IDP calls",
|
|
"multiSelect": false,
|
|
"options": [
|
|
{
|
|
"label": "Fix with Promise.all in this PR (Recommended)",
|
|
"description": "Wrap the 5 independent IDP calls in Promise.all(). The plan itself calls this 'trivial' and 'calls are independent.' With CC, this is a ~5-minute change. Leaving it sequential while doing a full auth refactor is the wrong time to ignore a known bottleneck. (human: ~30min / CC: ~5min)"
|
|
},
|
|
{
|
|
"label": "Defer to a follow-up PR",
|
|
"description": "Add a TODO and ship the refactor without the optimization. Acceptable if the IDP calls are already fast enough at current scale and you want to keep the diff minimal. (human: 0 now / CC: 0 now, but requires a follow-up task)"
|
|
}
|
|
]
|
|
}
|
|
],
|
|
"answered": true,
|
|
"failed": false,
|
|
"answers": {
|
|
"D5 — Performance Issue 1: 5 sequential IDP calls per token validation. Fix with Promise.all in this PR or defer? <gstack-qid:plan-eng-perf-idp-parallel>": "Fix with Promise.all in this PR (Recommended)"
|
|
},
|
|
"unansweredQuestionIndices": [],
|
|
"answeredAt": "2026-09-09T05:58:59.871Z"
|
|
},
|
|
{
|
|
"sessionId": "4fc2a716-4122-4cd3-bc0e-1128cd9b9819",
|
|
"toolUseId": "toolu_01Pfq8t8yzTVsZUGQZdukwii",
|
|
"questions": [
|
|
{
|
|
"question": "D6 — TODO: Add IDP circuit breaker or retry strategy? The plan parallelizes IDP calls but does not address IDP unavailability. <gstack-qid:plan-eng-todo-circuit-breaker>",
|
|
"header": "TODO: IDP CB",
|
|
"multiSelect": false,
|
|
"options": [
|
|
{
|
|
"label": "Add to TODOS.md for later",
|
|
"description": "Capture it now so it is not forgotten, but do not scope it into this PR. Context: Promise.all failing on first IDP error means auth is non-functional during IDP brownouts. A circuit breaker (e.g. opossum library) or exponential-backoff retry would isolate failures. Depends on: T5 (IDP parallelization) being merged first."
|
|
},
|
|
{
|
|
"label": "Build it now in this PR",
|
|
"description": "Add a circuit breaker or retry wrapper around the IDP calls as part of this PR. Most natural time to add it since we are already refactoring the IDP call path. (human: ~3h / CC: ~20min)"
|
|
},
|
|
{
|
|
"label": "Skip — not valuable enough",
|
|
"description": "Acceptable if the IDP has its own HA/retry guarantees and application-level retries are not required by SLA."
|
|
}
|
|
]
|
|
}
|
|
],
|
|
"answered": true,
|
|
"failed": false,
|
|
"answers": {
|
|
"D6 — TODO: Add IDP circuit breaker or retry strategy? The plan parallelizes IDP calls but does not address IDP unavailability. <gstack-qid:plan-eng-todo-circuit-breaker>": "Add to TODOS.md for later"
|
|
},
|
|
"unansweredQuestionIndices": [],
|
|
"answeredAt": "2026-09-09T06:01:14.441Z"
|
|
},
|
|
{
|
|
"sessionId": "4fc2a716-4122-4cd3-bc0e-1128cd9b9819",
|
|
"toolUseId": "toolu_01Fc4jMYA8Nxj9ToEEp6ZjF9",
|
|
"questions": [
|
|
{
|
|
"question": "D7 — TODO: Distributed locking for AuthCache if running multi-instance? The in-process mutex from T1 only protects within a single process. <gstack-qid:plan-eng-todo-distributed-lock>",
|
|
"header": "TODO: dist lock",
|
|
"multiSelect": false,
|
|
"options": [
|
|
{
|
|
"label": "Add to TODOS.md for later",
|
|
"description": "Capture the gap: if AuthBroker + SessionMint run as multiple replicas, the mutex from T1 only serializes writes within one process. Cross-process writes to the shared cache can still race. A Redis lock or optimistic concurrency on the underlying adapter would fix it. Depends on: knowing the deployment topology."
|
|
},
|
|
{
|
|
"label": "Skip — not valuable enough",
|
|
"description": "Acceptable if the service runs as a single process or the underlying cache adapter already handles concurrent writes atomically (e.g. Redis SET NX). If the adapter is thread-safe and atomic, the in-process mutex is redundant anyway."
|
|
},
|
|
{
|
|
"label": "Investigate now before deciding",
|
|
"description": "Check if the existing cache adapter (mentioned in the plan) already provides atomic write semantics. If it does, neither the in-process mutex nor a distributed lock are needed for correctness."
|
|
}
|
|
]
|
|
}
|
|
],
|
|
"answered": true,
|
|
"failed": false,
|
|
"answers": {
|
|
"D7 — TODO: Distributed locking for AuthCache if running multi-instance? The in-process mutex from T1 only protects within a single process. <gstack-qid:plan-eng-todo-distributed-lock>": "Add to TODOS.md for later"
|
|
},
|
|
"unansweredQuestionIndices": [],
|
|
"answeredAt": "2026-09-09T06:01:24.472Z"
|
|
}
|
|
]
|
|
}
|
|
}
|